Modeling to support influenza vaccine development

Slides: https://www.andreashandel.com/presentations/

2025-02-18

Acknowledgements

  • Zane Billings, Savannah Hammerton, other group members
  • Collaborators, especially Ted Ross
  • NIH

Overview

  • Part 1: Vaccine response quantification

  • Part 2: Correlates of protection for animals

Part 1: Vaccine response quantification

Motivation

  • We need to be able to evaluate and compare existing and new influenza vaccines.
  • Immunogenicity is often a good correlate for protection. For flu specifically, HA antibodies.
  • To assess broad protection, we need to quantify antibody responses to a panel of flu strains.

Quantifying vaccine responses

Quantifying vaccine responses

Quantifying vaccine responses

Comparing vaccine responses

A new method to quantify/compare vaccine responses

  • Organize strains by antigenic distance
  • Fit a model to more robustly estimate magnitude/breadth/strength

Strain distance

Quantifying vaccine responses

Comparing vaccine responses

Testing our method

We sampled from the panel of heterologous strains from UGAFluVac to mimic different labs

Testing our method - the results

Part 1 Summary & Discussion

  • Our proposed new method seems to be more robust and suitable to quantify and compare vaccine responses.
  • We would like to compare the method across actual separate studies.
  • Include ‘future’ strains into analysis.
  • Compare different distance measures.
  • Explore models beyond linear.

Part 2: Correlates of protection for animals

Motivation

  • Pre-clinical/animal studies are an important part of the vaccine development pathway.
  • Results in animals inform choices for subsequent human studies.
  • We need to be able to properly assess influenza vaccine efficacy in animals.

Motivation

  • For both humans and animals, vaccine protection from infection/disease is the gold standard.
  • Immunogenicity is often a good correlate of protection (CoP). For flu specifically, HA antibodies.
  • CoP in humans are only somewhat understood. They are even less studied in animals.

CoP in adults

Hobson et al.: https://pmc.ncbi.nlm.nih.gov/articles/PMC2130285/

CoP in children

Ng et al.: https://pubmed.ncbi.nlm.nih.gov/23908481/

CoP meta-analysis

Coudeville et al.: https://pubmed.ncbi.nlm.nih.gov/20210985/

CoP in animals

  • What’s the relation between antibody titers and outcomes?
  • Does a 1:40 titer correspond to 50% protection in mice, ferrets, guinea pigs, etc.?

CoP in mice

Jacobsen et al.: https://pubmed.ncbi.nlm.nih.gov/28928215/

CoP in ferrets

Wong et al.: https://pubmed.ncbi.nlm.nih.gov/28303960/

Part 2 Summary & Discussion

  • Not much known about CoP in animals.
  • We could model the mapping from CoP to outcomes with the right kind of data:
    • CoP data: antibody (and/or other immunological) measurements in non-naive animals prior to challenge
    • Outcome data: Infection, weight loss, symptoms, viral load, etc.
  • Broader: Relation between CoP in animals to CoP in humans?